Bedside estimation of risk as an aid for decision-making in cardiac surgery

Abstract

Background: Evaluations of the cardiac-surgery mortality rates of hospitals and surgeons can be fair and realistic only when the observed mortality rates are compared with expected rates with preoperative risk factors taken into account. Risk-approximation calculations also can assist patients and physicians in discussing the risk of cardiac surgery, especially if the estimation of surgical mortality takes all of the important risk factors into account.

Methods: A logistic regression model was developed in which 47 potential risk factors were considered, and a method requiring only simple addition and graphic interpretation was designed for approximating the estimated risk easily and quickly, with paper and pencil alone.

Results: The estimates provided by the simplified model correlated well with the observed mortality rates.

Conclusions: A simple approximation of a logistic regression model has been found to be helpful in discussions between physicians and patients contemplating aortocoronary bypass or valve-related surgery.